Trust in the scientific research community predicts intent to comply with COVID-19 prevention measures: An analysis of a large-scale international survey dataset

Abstract

In the present study, I explored the relationship between people's trust in different agents related to prevention of spread of COVID-19 and their compliance with pharmaceutical and nonpharmaceutical preventive measures. The COVIDiSTRESSII Global Survey dataset, which was collected from international samples, was analysed to examine the aforementioned relationship across different countries. For data-driven exploration, network analysis and Bayesian generalized linear model (GLM) analysis were performed. The result from network analysis demonstrated that trust in the scientific research community was most central in the network of trust and compliance. In addition, the outcome from Bayesian GLM analysis indicated that the same factor, trust in the scientific research community, was most fundamental in predicting participants' intent to comply with both pharmaceutical and non-pharmaceutical preventive measures. I briefly discussed the implications of the findings, the importance of trust in the scientific research community in explaining people's compliance with measure to prevent spread of COVID-19.

Validity testing of the conspiratorial thinking and anti-expert sentiment scales during the COVID-19 pandemic across 24 languages from a large-scale global dataset

“…Specifically, doubters and deniers of COVID-19 risk tended to believe conspiracy theories related to the pandemic, expressed anti-elitist sentiments and reported low compliance with measures to reduce the spread of the virus [ 12 ]. Low trust in institutions, including the scientific community, is also linked to vaccine hesitancy as well as compliance with preventive measures in general [ 15 – 17 ]. Finally, conspiracy theories and negative attitudes towards experts have other detrimental effects such as increasing uncertainty and discrimination against marginalised groups [ 9 ].…”

“…The presence of scalar invariance, which assumes the same factor loadings and intercepts across groups, is essential to assure the quality of cross-national research using the scales [ 29 ]. Measurement alignment was performed to address the potential issue of measurement non-invariance reported by the measurement invariance test as done in prior COVID-19-related international survey studies if needed [ 15 ]. The measurement alignment process was expected to address non-invariance so that researchers would be able to conduct cross-national comparison.…”

Predictors of Compliance with COVID-19 Guidelines Across Countries: The role of social norms, moral values, trust, stress, and demographic factors

“…Monte Carlo simulations (on randomly generated datasets with 500 iterations each; N1 = 100, N2= 200, N3 = 500) were also performed to test whether alignment was completed in a reliable and consistent manner. In this process, the correlation coefficients between factor means and factor variances, obtained from MG-CFA and multigroup alignment, R 2 loadings and R 2 intercepts, respectively, were examined (values higher than .95 were considered satisfactory, Han et al, 2022).…”

“…For H2 and H3, items from SF-MFQ and Trust in Institutions were entered into models individually instead of one composed score reflecting the underlying latent construct. To reduce the complexity of the models, we performed Bayesian Generalised Linear Model (GLM) before MLM to identify which indicators should be included in the models by comparing all possible models with predictors of interest including country as a random effect (Han, 2022). The decision was made by exploring which model demonstrated the highest BF from Bayesian GLM.…”

Using Normative Language When Describing Scientific Findings: Protocol for a Randomized Controlled Trial of Effects on Trust and Credibility

“…At the same time, even though trust is defined and measured in a variety of different ways, studies conducted across multiple different populations have identified associations between trust in science and intention to get vaccinated or boosted for COVID-19 [8][9][10][11][12], as well as adherence to other measures to mitigate harm from the pandemic (eg, nonpharmaceutical interventions) [13][14][15][16][17]. Thus, even if the exact nature of the relationship is unclear, it is reasonable to speculate that trust in science and scientists is associated with people's behaviors during a public health emergency such as COVID-19.…”